code: def test_correct_results(self, _, in_type, mean, std):
      seed = 0
      rician_fn = RandRicianNoise(prob=1.0, mean=mean, std=std)
      rician_fn.set_random_state(seed)
      im = in_type(self.imt)
      noised = rician_fn(im)
      if isinstance(im, torch.Tensor):
          self.assertEqual(im.dtype, noised.dtype)
      np.random.seed(seed)
      np.random.random()
      _std = np.random.uniform(0, std)
      expected = np.sqrt(
          (self.imt + np.random.normal(mean, _std, size=self.imt.shape))
          ** 2
          + np.random.normal(mean, _std, size=self.imt.shape) ** 2
      )
      if isinstance(noised, torch.Tensor):
          noised = noised.cpu()
      np.testing.assert_allclose(expected, noised, atol=1e-5)
  
file_path: MONAI/tests/test_rand_rician_noise.py
imports: from __future__ import annotations
  import unittest
  import numpy
  import torch
  from parameterized import parameterized
  from monai.transforms import RandRicianNoise
  from tests.utils import TEST_NDARRAYS, NumpyImageTestCase2D
label_desc: Use image node_id 1 for calling the TestRandRicianNoise obj's underlying member method code with example usage: obj.test_correct_results(_, in_type, mean, std) without return types